Try Bagel AI - The All-in-One Multimodal AI Model

Transform your images with AI-powered editing

Upload JPG/PNG/WEBP images up to 10MB, with a minimum width/height of 300px.
0/1000
Credits required: 0.5

Sample Result

Upload an image and add editing instructions to get started

Bagel AI Image Editing Examples

See how Bagel AI transforms images with natural language instructions

Input Image
input image

Instruction

add vibrant colors to this black and white image

Bagel AI Output
output image

Three AI Capabilities in One Bagel AI Model

Unlike traditional AI tools that specialize in single tasks, Bagel AI seamlessly handles image generation from text, instruction-based image editing, and comprehensive image understanding - all within one unified multimodal model.

Emerging Properties Through Unified Training

Bagel AI demonstrates remarkable emerging properties developed during unified multimodal pretraining. As the model scaled, it naturally developed sophisticated capabilities including intelligent editing that requires deep visual reasoning.

How to Use Bagel AI for Multimodal Tasks

Bagel AI is designed to be intuitive and powerful, offering three core capabilities in one unified model: image generation, editing, and understanding.

Step 1

Choose Your Task Select from Bagel AI's three main capabilities: text-to-image generation, image editing with instructions, or image understanding and analysis.

Step 2

Provide Your Input For generation, use text prompts. For editing, upload an image with natural language instructions. For understanding, upload an image with your questions about it.

Step 3

AI Processing with Bagel AI Bagel AI's advanced 7B parameter model processes your input using its unified multimodal architecture, delivering high-quality results across all tasks.

Step 4

Get Your Results Download generated or edited images, or receive detailed analysis and answers about your uploaded images from Bagel AI's understanding capabilities.

Try Bagel AI Now

FAQ

Bagel AI is ByteDance Seed's revolutionary unified multimodal AI model with 7B parameters that combines three essential capabilities: text-to-image generation, instruction-based image editing, and comprehensive image understanding in a single model.
Bagel AI uses a Mixture-of-Transformer-Experts (MoT) architecture with dual visual encoders - a VAE for pixel-level details and a ViT for semantic understanding. This allows Bagel AI to process both text and visual tokens seamlessly across different tasks.
Unlike specialized AI models that focus on single tasks, Bagel AI is a unified multimodal model that naturally developed multiple capabilities during training. It can generate, edit, and understand images without switching between different models.
Bagel AI offers three core capabilities: 1) Text-to-image generation with quality competitive to Stable Diffusion 3, 2) Instruction-based image editing, and 3) Image understanding and analysis with detailed explanations.
Bagel AI demonstrates competitive performance across all tasks: it outperforms Qwen2.5-VL-7B on vision-language benchmarks, matches SD3-Medium in text-to-image generation, and excels in image editing compared to leading open-source models.
Bagel AI features advanced chain-of-thought reasoning capabilities that allow the model to think through complex problems step-by-step before generating responses, resulting in more sophisticated and accurate outputs.
Yes, Bagel AI is licensed under Apache 2.0, making it suitable for commercial use. You can integrate Bagel AI into your workflows and applications for business purposes.
Bagel AI requires powerful GPU hardware with 40GB+ VRAM for optimal performance. A100 or H100 GPUs are recommended for running the full Bagel AI model locally.
You can start using Bagel AI through various platforms including Replicate, or explore the model weights and documentation on the official Bagel AI website and GitHub repository.
Bagel AI uses MoT architecture with 7B active parameters from a total of 14B parameters. This design allows the model to efficiently handle different types of tasks while maintaining high performance across all multimodal capabilities.
Yes, Bagel AI supports various image formats and can work with different styles including photorealistic, artistic, and illustrated images. The model's dual encoder system enables comprehensive understanding of both pixel-level and semantic information.

Ready to Experience the Future with Bagel AI?

Join the revolution in multimodal AI with Bagel AI from ByteDance Seed. Whether you're generating images from text, editing with natural language instructions, or analyzing visual content, Bagel AI provides unmatched versatility in a single unified model.